Hi R-devel,
If you did read my survey on Rhelp about reporting, you may have seen that
I am implementing a way to handle outputs for R (mainly target output
destinations: xHTML and TeX).
In fact: I does have something that works for basic objects, entirely done
with S4 classes, with the results visible at:
http://www.stat.ucl.ac.be/ROMA/sample.htmhttp://www.stat.ucl.ac.be/ROMA/sample.pdf
To achieve this goal, I do use intermediary objects that would reprensent
the structure of the output. Thus I defined classes for Vector, Tables,
Rows, Cells, Sections, and so on. Most of those structure are recursive.
Then, at a firts attemps, a matrix would be represented as a Table
containing Rows containg Cells containing Vectors, which finally is easy to
export and which makes easy the customisation (if you need to insert a
footnote within a cell for example).
I know that this intermediary layout would be far more easier to handle at
C level, but I dont have any C skill for that...
One of my problem is that this consumes a lot of memory/computation time.
Too much, indeed...
20 sec. to export data(iris) on my PIV 3.2 Ghz 1Go RAM, which is not
acceptable.
I was intending to do start properly, as starting from scratch new code. I
did write everything using S4 classes.
Doing a simple test reveals crucial efficiency differences between S3 and
S4 classes.
Here is the test:
---
### S3 CLASSES
S3content <- function(obj=NULL,add1=NULL,add2=NULL,type="",...){
out <- list(content=obj,add1=add2,add2=add2,type=type)
class(out) <- "S3Content"
return(out)
}
S3vector <- function(vec,...){
out <- S3content(obj=vec,type="Vector",...)
class(out) <- "S3Vector"
return(out)
}
### S4 classes
setClass("S4content",representation(content="ANY",add1="ANY",add2="ANY",type="character"))
S4content <- function(obj=NULL,add1=NULL,add2=NULL,type="",...){
new("S4content",content=obj,add1=add1,add2=add2,type=type)
}
S4vector <- function(vec,...){
new("S4content",type="vector",content=vec,...)
}
### Now the test
> test <- rnorm(10000)
> gc()
used (Mb) gc trigger (Mb)
Ncells 169135 4.6 531268 14.2
Vcells 75260 0.6 786432 6.0
> (system.time(lapply(test,S3vector)))
[1] 0.17 0.00 0.19 NA NA
> gc()
used (Mb) gc trigger (Mb)
Ncells 169136 4.6 531268 14.2
Vcells 75266 0.6 786432 6.0
> (system.time(lapply(test,S4vector)))
[1] 15.08 0.00 15.13 NA NA
-----
There is here a factor higher than 80!
Is there something trivial I did overlook?
Is this 80 factor normal?
Is it still recommended (recommendable...) to use S4 classes when
considered that?
Eric
Eric Lecoutre
UCL / Institut de Statistique
Voie du Roman Pays, 20
1348 Louvain-la-Neuve
Belgium
tel: (+32)(0)10473050
lecoutre at stat.ucl.ac.behttp://www.stat.ucl.ac.be/ISpersonnel/lecoutre
If the statistics are boring, then you've got the wrong numbers. -Edward
Tufte